Chained Lin-Kernighan for Large Traveling Salesman Problems
INFORMS Journal on Computing
Tunneling between optima: partition crossover for the traveling salesman problem
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
On complexity of the optimal recombination for the travelling salesman problem
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Exploiting decomposability using recombination in genetic algorithms: an exploratory discussion
SSBSE'11 Proceedings of the Third international conference on Search based software engineering
Improving Lin-Kernighan-Helsgaun with crossover on clustered instances of the TSP
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
A Powerful Genetic Algorithm Using Edge Assembly Crossover for the Traveling Salesman Problem
INFORMS Journal on Computing
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We present a hybrid genetic algorithm that incorporates the Generalized Partition Crossover (GPX) operator to produce an algorithm that is competitive with the state of the art for the Traveling Salesman Problem (TSP). GPX is respectful, transmits alleles and is capable of tunneling directly to new local optima. Our results show that the hybrid genetic algorithm quickly finds optimal and near optimal solution on problems ranging from 500 to 1817 cities using a population size of 10. It is also superior to Chained-LK given similar computational effort. Additional analysis shows that all the edges found in the globally optimal solution are present in a population after only a few generations in almost every run. Furthermore the number of unique edges in the population is also less than twice the problem size.